Insert a blank row after each group of data

Question

This question has been asked for excel. How to automatically insert a blank row after a group of data

I would like to know if there is a function for doing the same in R.

example:

group <- c("a","b","b","c","c","c","d","d","d","d")
xvalue <- c(16:25)
yvalue <- c(1:10)
df <- data.frame(cbind(group,xvalue,yvalue))
   group xvalue yvalue
1      a     16      1
2      b     17      2
3      b     18      3
4      c     19      4
5      c     20      5
6      c     21      6
7      d     22      7
8      d     23      8
9      d     24      9
10     d     25     10

I would like to have a blank row after each group so that I can check the entries manually

   group xvalue yvalue
1      a     16      1
2
3      b     17      2
4      b     18      3
5
6      c     19      4
7      c     20      5
8      c     21      6
9
10     d     22      7
11     d     23      8
12     d     24      9
12     d     25     10

thanks

Answer 1

First transform all columns to character vectors:

df_new <- as.data.frame(lapply(df, as.character), stringsAsFactors = FALSE)

Then you can create the output you're looking for:

head(do.call(rbind, by(df_new, df$group, rbind, "")), -1 )

#      group xvalue yvalue
# a.1      a     16      1
# a.2                     
# b.2      b     17      2
# b.3      b     18      3
# b.31                    
# c.4      c     19      4
# c.5      c     20      5
# c.6      c     21      6
# c.41                    
# d.7      d     22      7
# d.8      d     23      8
# d.9      d     24      9
# d.10     d     25     10

Answer 2

Sven has answered exactly what you've asked for, but I think what you want to do is a generally bad idea.

If visual separation is all that you are hoping to achieve, I would recommend just using split:

split(df, df$group)
# $a
#   group xvalue yvalue
# 1     a     16      1
#
# $b
#   group xvalue yvalue
# 2     b     17      2
# 3     b     18      3
#
# $c
#   group xvalue yvalue
# 4     c     19      4
# 5     c     20      5
# 6     c     21      6
#
# $d
#    group xvalue yvalue
# 7      d     22      7
# 8      d     23      8
# 9      d     24      9
# 10     d     25     10

This has the advantages of (1) visual separation, (2) easy indexing, (3) no conversion of your data, and (4) allowing you to run the same functions on different subsets of your data.